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UI Screens Record Quality Audit + Base-100 Series
x402
UI Screens Record Quality Audit + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Runs a record quality audit and Base-100 index series on supplied UI screen data (widget_count, render_ms) for up to 200 rows, returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
UI screens — Record quality audit + Base-100 series: Record quality audit + Base-100 series for supplied ui screens records (widget_count, render_ms). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns 2 independent reports: (1) a record quality audit assessing completeness, validity, and anomalies in the supplied UI screen rows, and (2) a Base-100 index series for the selected numeric field (widget_count or render_ms), computed locally with no external lookups. Both reports cover up to 200 supplied rows.
Example use cases
Game UI widget quality audit
“I have 50 rows of UI screen data from my game — each row has a game area, a date, widget_count, and render_ms. Can you run a record quality audit and base-100 series on widget_count, using row 0 as the base index?”
Render performance index analysis
“Can you analyze this batch of 120 UI screen records and give me a base-100 series on render_ms starting from index 0, plus a quality audit to flag any bad records?”
Pre-launch data validation for UI screens
“Before I ship, I need a quality audit on my UI screen dataset — 80 rows with widget_count and render_ms per game area and date. Index on widget_count from row 0 and tell me if anything looks off.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-16-012?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have UI screen records with widget_count and render_ms fields and need both a data quality audit and a base-100 normalized index series in a single low-cost call. It is ideal for game analytics pipelines, UI performance validation, or pre-release data checks where you want two bundled local analytical reports without any external data enrichment or live predictions.
Side effects
- Empty rows array or missing required fields (row_id, game_area, date, widget_count, render_ms) causes validation failure
- More than 200 rows supplied exceeds maxItems limit
- base_index out of range (must be 0–199) causes parameter error
- Invalid date format (must be YYYY-MM-DD) causes rejection
- Non-numeric values for widget_count or render_ms where numbers are expected
- Payment of 0.01 USDC not completed via x402 protocol results in 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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